About Us

WereHitachi Vantara a global infrastructure business. Our people are the force of meaningful progress. We enable theincredible with data from taking theme park fans on magical rides conserving natural resources protecting rainforests to saving lives. We empower businesses to automateoptimize and advance innovation. Together we create a sustainable future for all.

Imagine the sheer breadth of talent it takes to inspire the future. Wedontexpect you to fit every requirement your life experience character perspective and passion for achievinggreat thingsin the world are equally important to us.

Role Overview

Hitachi Vantara is seeking anAI SDETto join our Global Quality Assurance this role you will design and execute test strategies forAIdrivensystems includingLLMpoweredfeatures machine learning components and intelligent automation workflows.

You will collaborate closely with product teams data scientists ML engineers and platform teams tovalidateAI behavior across the full lifecyclefrom data ingestion and model inference to system integration anduserfacingfunctionality. This includes evaluating model outputs ensuring reliability and safetyvalidatingdata pipelines and building tooling that supports predictablehighqualityAI experiences.

This role is ideal for an engineer who enjoys blending software testing system integration and applied AI behavior analysis.

Experience:710 Years
Job Location:Kolkata India preferred

Key Responsibilities

• AI System Validation:Test andvalidateAI/ML features across internal models embedded AI components and integrated AI services.

• Model Behavior Evaluation:Assess model inference quality prompt/response behavior performance safety and robustness across diverse scenarios.

• Data Pipeline & Schema Verification:Validatedata contracts feature schemas and payload structures used by AI models and downstream systems.

• EndtoEndWorkflow Testing:EnsureAIdrivenworkflows function reliably across internal components orchestration layers anduserfacingapplications.

• Tooling & Automation:Build tools to simulate AI behavior automate evaluation workflows generate test datasets and support continuous validation.

• AI Quality & Reliability:Identifyedge cases failure modes drift indicators and quality gaps inAIpoweredfeatures.

• Security & Responsible AI Checks:Validatecompliance with security privacy fairness and responsible AI guidelines.

• CrossFunctionalCollaboration:Work with product engineering and data science teams to troubleshoot issuesvalidatefixes and improve AI feature readiness.

• Documentation:Produce clear documentation for AI test plans expected behaviors evaluation criteria and validation procedures.

• Continuous Improvement:Propose enhancements to improve AI reliability observability and test coverage across the lifecycle.

Required Skills

• 710 years of experience in software testing or SDET roles with 2 years focused on AI/ML systems.

• StrongproficiencyinPythonfor test development data validation andevaluationtooling.

• Strong foundational knowledge ofstorage technologies such as block storage object storage (S3compatible systems) NFS or distributed file systems.

• KnowledgeofHitachi products such as VSP360 OpsCenter will be an added advantage.

• Experience with AI/ML frameworks or platforms such asPyTorch TensorFlowScikitlearn Hugging Face Azure AI AWS AI/ML or Google Vertex AI.

• Understanding of AI/ML concepts including:

• model inference behavior

• evaluation metrics

• prompt/response quality

• drift bias and fairness considerations

• Experience testingLLMbasedsystems orMLpoweredfeatures.

• Familiarity withMLOpstools and workflows (MLflow Kubeflow SageMaker Vertex AI etc.).

• Strong understanding of QA methodologies SDLC and agile practices.

• Experience with Linux/UNIX environments and containerized workflows (Docker).

• Excellent communication skills and ability to collaborate across global teams.

Preferred Qualifications (AIFocusedCertifications)

• Microsoft Certified: Azure AI Engineer Associate

• AWS Certified Machine Learning Specialty

• Google Professional Machine Learning Engineer

• NVIDIA Deep Learning Institute Certifications (LLMs generative AI computer vision)

• TensorFlow Developer Certificate

• Hugging Face NLP/LLM Certifications

• ISTQB Certified Tester AI Testing

• Certified Kubernetes Administrator (CKA) or CKAD

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